Anna Davidsson, Martin Hultman, Sofia Strid, Sebastian Svenberg (p), Christopher Ali Thorén

Sierdjan Koster

This paper aims to critically reflect on narrative interview methodology in relation to vulnerability profile of participants in a project about twin transition. A perspective on unequal access to green- and digital technologies will be developed from advancing the centre-periphery dimensions beyond purely regional aspects. The retelling of a process and carrying-out of interviews is told alongside comments on vulnerability and the meaning of inequality under conditions set by the simultaneous digital- and twin transition. The empirical data consists of the Nordic segment of a dataset with qualitative narrative interviews conducted within the project ST4TE, “Strategies for just and equitable transitions in Europe”. The access to green and digital technologies are understood through participants life-stories, anecdotes, relational understandings of self, and the caring for others in challenging or turbulent times. Reflection about the content of the interviews will be done in parallel with reflections on the ability to explore experiences of inequality through narrative interviews as research practice. The centre-periphery dimension is presented as a framework that can be used to problematise relationship between researcher and participant, urban and rural, activity and passivity, and the process character of vulnerability.

Femke Cnossen, Sierdjan Koster (p)

Deyu Li

This research examines the differentiated regional exposure to new technologies across Europe. Over the past 40 years, biased technological change, particularly the rise of computer technologies, has led to declining employment in routine occupations, with varying local impacts; some regions benefit, while other struggle. Recent adoption of AI-technologies will likely bring equally significant and regionally varied employment effects. With this as a backdrop, we assess regional exposure to AI, software, and robots by linking occupation-level exposure measures to NUTS-2 regions. Using data from the European Union Labour Force Survey, we show that i) AI exposure is particularly high in high-skilled regions and Robots and Software exposure in low- and middle educated areas and ii) that there are stark differences between Western/Northern regions and Eastern/Southern regions in the EU with the latter typically showing greater exposure to technology.

Deyu Li (p), Benjamin Cornejo Costas

Anastasia Panori

The green transition has been in the core of EU policy agenda especially since the COVID-19 pandemic. However, existing studies of green transition based on patent data provided limited insights for further understanding whether the green transition is also a just transition that provide good job opportunities for achieving inclusive growth. A focus on jobs and skills is therefore important for better understanding the directionality of the green transition.
Recent studies on green jobs have applied the task-based approach in categorizing the jobs into green and non-green jobs based on the intensity of green skills or tasks in each occupation and compared the green jobs with other jobs in terms skill requirements and wages. Although this approach avoided defining green jobs at the occupation level, it failed to capture the complementarity between non-green skills and green skills.
This paper links green patents with the European classification of skills, competences, qualifications and occupations (ESCO) based on the semantic similarities using recent natural language processing methods. Doing so, we will be able to capture a broader set of skills that are related to the green transition. This is especially important because many non-green skills including many digital skills are expected to play an important role in facilitating further penetration of clean energy technologies to achieve the net-zero goal.
Furthermore, this paper combines data from the European Labor Force Survey and the online job advertisement data provided by the European Centre for the Development of Vocational Training (CEFEDOP) to calculate the availability of skills that are relevant for the green transition of European regions. This comprehensive mapping of the skills and jobs for the green transitions at the European regional level can provide important insights for policies that aimed at promoting sustainable and inclusive development.

Vicente Royuela, Anastasia Panori (p), Jordi Lopez Tamayo

Sebastian Svenberg

Regional attractiveness is a concept that encompasses the various factors and characteristics that make a particular geographic area appealing and desirable to individuals. These factors may include economic opportunities, social well-being and quality of life making the concept of regional attractiveness dynamic and multi-layered. Hence, regional characteristics play an essential role in making regions capable of keeping their existing human capital and attracting new forms of activity as well as specific groups of people. Connecting the notion of regional attractiveness to the Twin Transition is essential, as the latter has recently shaped policy discussions and choices within the European context. Thus, it is important to explore how green and digital factors may affect individual choices on spatial mobility, and therefore, their impact on the developmental dynamics of the regions.
Research shows that green and digital transitions have significant indirect effects on individual mobility and regional development, often intensifying existing spatial inequalities. The green transition redistributes economic and social assets, leading to the concentration of green technologies, employment, and innovation in regions better equipped for sustainable economic activities, while less developed areas struggle with unemployment, skill mismatches, and brain drain. Simultaneously, the digital transition reshapes accessibility and connectivity, influencing migration patterns, yet rural communities often face barriers such as limited digital skills or resistance to change. These shifts affect regional attractiveness, as urban and capital regions that swiftly adopt green policies and digital infrastructure attract more talent and investment, further widening the gap with rural or declining industrial areas. Without effective integration of the green and digital transformations, rising inequalities between EU regions in terms of their ability to attract human capital will become a significant barrier for achieving even developmental opportunities, leading to the emergence and persistence of lagging regions.
The Regional Attractiveness Index aims at exploring how traditional, digital, and green factors jointly determine regional attractiveness. The results indicate that northern and western Europe generally outperforms southern and eastern regions across traditional, digital, and green dimensions. Predominantly urban regions consistently rank higher than rural ones, both in traditional factors (employment opportunities, institutional quality) and emerging domains (digital connectivity, sustainability initiatives). Moreover, men seem to be more influenced by digital opportunities, whereas women often prioritize environmental sustainability and quality-of-life factors. Finally, sensitivity tests show that overweighting digital or green factors can enhance some regions’ standing while reducing others’, further illustrating the context-dependent nature of regional attractiveness.